Canonical variate analysis for performance degradation under faulty conditions

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dc.contributor.authorRuiz Cárcel, Cristóbal
dc.contributor.authorLao, Liyun
dc.contributor.authorCao, Yi
dc.contributor.authorMba, David
dc.date.accessioned2016-07-26T14:47:49Z
dc.date.available2016-07-26T14:47:49Z
dc.date.issued2016-06-01
dc.description.abstractCondition monitoring of industrial processes can minimize maintenance and operating costs while increasing the process safety and enhancing the quality of the product. In order to achieve these goals it is necessary not only to detect and diagnose process faults, but also to react to them by scheduling the maintenance and production according to the condition of the process. The objective of this investigation is to test the capabilities of canonical variate analysis (CVA) to estimate performance degradation and predict the behavior of a system affected by faults. Process data was acquired from a large-scale experimental multiphase flow facility operated under changing operational conditions where process faults were seeded. The results suggest that CVA can be used effectively to evaluate how faults affect the process variables in comparison to normal operation. The method also predicted future process behavior after the appearance of faults, modeling the system using data collected during the early stages of degradation.en_UK
dc.identifier.citationC. Ruiz-Cárcel, L. Lao, Y. Cao, D. Mba, Canonical variate analysis for performance degradation under faulty conditions, Control Engineering Practice, Volume 54, September 2016, pp70-80en_UK
dc.identifier.issn0967-0661
dc.identifier.urihttp://dx.doi.org/10.1016/j.conengprac.2016.05.018
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/10177
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectFault detectionen_UK
dc.subjectFault diagnosisen_UK
dc.subjectSystem identificationen_UK
dc.subjectMultivariate analysisen_UK
dc.subjectCanonical variateen_UK
dc.subjectExperimental studyen_UK
dc.titleCanonical variate analysis for performance degradation under faulty conditionsen_UK
dc.typeArticleen_UK

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